activity
20242026
collaborators

14 papers

cs.MA2026

Bayesian Partner Modelling enables Adaptive Replanning for LLM Coordination

Harsh Goel, Aditya Sai Ellendula, Vaishnav Tadiparthi +3

Multi-agent Large Language Model (LLM) systems often struggle to collaborate with new teammates whose strategies shift mid-task. Because agents execute multi-step or temporally ext…

cs.CV2026

Incentivizing Vision Language Models to Search for Long Video Question Answering

Harsh Goel, S P Sharan, Sahil Shah +4

We introduce VSeek, an agentic framework that transforms long-video question answering (LVQA) from a passive, single-pass perception task into a multi-turn retrieval process. VSeek…

cs.LG2026

-R1: Learning to Retrieve and Answer Step-by-Step with Synthetic Data

Harsh Goel, Akhil Udathu, Susmija Jabbireddy +2

Reinforcement learning (RL) post-training has enabled newer capabilities in models, such as agentic tool-use for search. However, these models struggle primarily due to limitations…

cs.MA2026

R3DM: Enabling Role Discovery and Diversity Through Dynamics Models in Multi-agent Reinforcement Learning

Harsh Goel, Mohammad Omama, Behdad Chalaki +3

Multi-agent reinforcement learning (MARL) has achieved significant progress in large-scale traffic control, autonomous vehicles, and robotics. Drawing inspiration from biological s…

cs.CV2026

We'll Fix it in Post: Improving Text-to-Video Generation with Neuro-Symbolic Feedback

Minkyu Choi, S P Sharan, Harsh Goel +2

Current text-to-video (T2V) generation models are increasingly popular due to their ability to produce coherent videos from textual prompts. However, these models often struggle to…

cs.LG2026

CoordLight: Learning Decentralized Coordination for Network-Wide Traffic Signal Control

Yifeng Zhang, Harsh Goel, Peizhuo Li +3

Adaptive traffic signal control (ATSC) is crucial in alleviating congestion, maximizing throughput and promoting sustainable mobility in ever-expanding cities. Multi-Agent Reinforc…